CLWD: a Chinese histopathology dataset for lung adenocarcinoma subtype classification
Effective diagnosis and treatment of lung adenocarcinoma depends on accurate typing, subtyping, and grading. Herein, we present the CLWD dataset, a valuable resource for the lung cancer pathology community, comprising 408 whole-slide images (WSIs) from 210 patients specifically curated for the study of lung adenocarcinoma subtypes. Scanned at 80 × magnification, it is one of the largest datasets in Asia, with a particular emphasis on Chinese patient demographics. Notably, the dataset includes comprehensive clinical information, such as age, sex, and diagnosis, providing a robust foundation for diverse research needs. Publicly accessible, it supports a range of applications, including machine learning model development and validation. An initial evaluation of lung adenocarcinoma subtype classification using a multi-instance learning framework demonstrated that this dataset can substantially advance global research and improve the accuracy of subtype diagnosis.
Authors
- Jun Ni (ORCID: https://orcid.org/0000-0002-7105-8475)
- Dapeng Tao (ORCID: https://orcid.org/0000-0003-0783-5273)
- Lei Li (ORCID: https://orcid.org/0000-0001-8723-3461)
- Jubo Peng
- Peiren Tang
- Ying Li
- Haoyun Zhao
- Yinghan Jiang
- Li Wang
- Jie Li
- Rongsheng Liu
- Yang Chen
Institutions
- Yunnan University (CN)
- Kunming Medical University (CN)
- First People's Hospital of Yunnan Province (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2026-03-05
- DOI
- https://doi.org/10.1038/s41597-026-06906-z
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Kunming Medical University
- Kunming University of Science and Technology